Fingerprint Matching using the Onion Peeling Approach and Turning Function

Fingerprint, as one of the most popular and robust biometric traits, can be used in automatic identification and verification systems to identify individuals. Fingerprint matching is a vital and challenging issue in fingerprint recognition systems. Most fingerprint matching algorithms are minutiae-based. The minutiae in fingerprints can be determined by their discontinuity. Ridge ending and ridge bifurcation are two frequently used minutiae in most fingerprint-based matching algorithms. This paper presents a new minutiae-based fingerprint matching using the onion peeling approach. In the proposed method, fingerprints are aligned to find the matched minutiae points. Then, the nested convex polygons of matched minutiae points are constructed and the comparison between peer-to-peer polygons is performed by the turning function distance. Simplicity, accuracy, and low time complexity of the Onion peeling approach are three important factors that make it a standard method for fingerprint matching purposes. The performance of the proposed algorithm is evaluated on the database $FVC2002$. The results show that fingerprints of the same fingers have higher scores than different fingers. Since the fingerprints that the difference between the number of their layers is more than $2$ and the minutiae matching score lower than 0.15 are ignored, the better results are obtained.